The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
권호 표지
DOI QR코드

DOI QR Code

Adaptive quantization for effective data-rate reduction in ultrafast ultrasound imaging

초고속 초음파 영상의 효과적인 데이터율 저감을 위한 적응 양자화

  • Doyoung Jang (School of Electronics and Electrical Engineering, Dankook University) ;
  • Heechul Yoon (School of Electronics and Electrical Engineering, Dankook University)
  • 장도영 (단국대학교 전자전기공학부) ;
  • 윤희철 (단국대학교 전자전기공학부)
  • Received : 2023.06.30
  • Accepted : 2023.08.17
  • Published : 2023.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Ultrafast ultrasound imaging has been applied to various imaging approaches, including shear wave elastography, ultrafast Doppler, and super-resolution imaging. However, these methods are still challenging in real-time implementation for three Dimension (3D) or portable applications because of their massive data rate required. In this paper, we proposed an adaptive quantization method that effectively reduces the data rate of large Radio Frequency (RF) data. In soft tissue, ultrasound backscatter signals require a high dynamic range, and thus typical quantization used in the current systems uses the quantization level of 10 bits to 14 bits. To alleviate the quantization level to expand the application of ultrafast ultrasound imaging, this study proposed a depth-sectional quantization approach that reduces the quantization errors. For quantitative evaluation, Field II simulations, phantom experiments, and in vivo imaging were conducted and CNR, spatial resolution, and SSIM values were compared with the proposed method and fixed quantization method. We demonstrated that our proposed method is capable of effectively reducing the quantization level down to 3-bit while minimizing the image quality degradation.

초고속 초음파 영상은 탄성 영상, 초고속 도플러, 초해상도 영상과 같은 다양한 초음파 기반의 기능성 영상기술에 폭넓게 적용되고 있다. 하지만, 획득하는 데이터의 양이 많아 실시간 영상 재구성이나 3차원 또는 모바일 초음파 영상 응용으로의 확장이 제한된다. 본 논문은 적응 양자화 기법을 통해 초고속 초음파 영상으로 획득되는 대용량 Radio frequency(RF) 데이터의 전송 효율을 높이는 방법을 제안한다. 인체에서 반사된 초음파 신호는 높은 동적 범위를 가져 대부분의 현재 시스템에서 사용되는 고정 양자화 기법은 10 bits ~ 14 bits 이상의 높은 양자화 단계를 가진다. 양자화 단계 저감에 대한 화질 저하의 한계를 극복하기 위해, 본 연구는 영상 깊이에 따라 구간을 설정하고, 각 영역별 RF 데이터를 정규화하고 양자화하는 방안을 제안한다. 정량적인 검증을 위해, Field II 컴퓨터 모사 실험을 활용하여, 고정 양자화 방법과 제안하는 방법의 대조도 대 잡음 비, 공간 해상도 및 원본 대비 유사도를 비교하였다. 또한, 연구용 초음파 장비를 활용한 인체 모사 실험 및 인체 실험을 통해 최종 3-bit로 재구성한 영상에서도 제안하는 방법이 효과적으로 적용되는 것을 입증하였다.

Keywords

Acknowledgement

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2022R1C1C1012107). 이 논문은 2023년도 정부(산업통상자원부)의 재원으로 한국산업기술진흥원의 지원을 받아 수행된 연구임(P0017120, 2023년 산업혁신인재성장지원사업).

References

  1. R. M. S. Sigrist, J. Liau, A. El Kaffas, M. C. Chammas, and J. K. Willmann, "Ultrasound elastography: review of techniques and clinical applications," Theranostics. 7, 1303-1329 (2017). https://doi.org/10.7150/thno.18650
  2. J. Bercoff, G. Montaldo, T. Loupas, D. Savery, F. Meziere, M. Fink, and M. Tanter, "Ultrafast compound doppler imaging: providing full blood flow characterization," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 58, 134-147 (2011). https://doi.org/10.1109/TUFFC.2011.1780
  3. M. Tanter and M. Fink, "Ultrafast imaging in biomedical ultrasound," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 61, 102-119 (2014). https://doi.org/10.1109/TUFFC.2014.2882
  4. Y. Kim, J. Kim, C. Basoglu, and T. Winter, "Programmable ultrasound imaging using multimedia technologies: a next-generation ultrasound machine," IEEE Trans. Inf. Technol. Biomed. 1, 19-29 (1997). https://doi.org/10.1109/4233.594021
  5. V. Shamdasani, R. Managuli, S. Sikdar, and Y. Kim, "Ultrasound color-flow imaging on a programmable system," IEEE Trans. Inf. Technol. Biomed. 8, 191-199 (2004). https://doi.org/10.1109/TITB.2004.828881
  6. J.-L. Gennisson, J. Provost, T. Deffieux, C. Papadacci, M. Imbault, M. Pernot, and M. Tanter, "4-d ultrafast shear-wave imaging," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 62, 1059-1065 (2015). https://doi.org/10.1109/TUFFC.2014.006936
  7. G. David, J.-L. Robert, B. Zhang, and A. F. Laine, "Time domain compressive beam forming of ultrasound signals," J. Acoust. Soc. Am. 137, 2773-2784 (2015). https://doi.org/10.1121/1.4919302
  8. T. Chernyakova and Y. C. Eldar, "Fourier-domain beamforming: the path to compressed ultrasound imaging," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 61, 1252-1267 (2014). https://doi.org/10.1109/TUFFC.2014.3032
  9. C. Chen, G. A. G. M. Hendriks, R. J. G. van Sloun, H. H. G. Hansen, and C. L. de Korte, "Improved planewave ultrasound beamforming by incorporating angular weighting and coherent compounding in fourier domain," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 65, 749-765 (2018). https://doi.org/10.1109/TUFFC.2018.2811865
  10. M. Gasse, F. Millioz, E. Roux, D. Garcia, H. Liebgott, and D. Friboulet, "High-quality plane wave compounding using convolutional neural networks," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 64, 1637-1639 (2017). https://doi.org/10.1109/TUFFC.2017.2736890
  11. J. Zhang, Q. He, Y. Xiao, H. Zheng, C. Wang, and J. Luo, "Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network," Med. Image Anal. 70, 102018 (2021).
  12. R. G. Vaughan, N. L. Scott, and D. R. White, "The theory of bandpass sampling," IEEE Trans. Signal Process. 39, 1973-1984 (1991). https://doi.org/10.1109/78.134430
  13. M. Mishali and Y. C. Eldar, "Sub-nyquist sampling: Bridging theory and practice," IEEE Signal Process. Mag. 28, 98-124 (2011). https://doi.org/10.1109/MSP.2011.942308
  14. J. Kang, H. Yoon, C. Yoon, and S. Y. Emelianov, "High-frequency ultrasound imaging with sub-nyquist sampling," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 69, 2001-2009 (2022). https://doi.org/10.1109/TUFFC.2022.3167726
  15. P.-C. Huang and P.-C. Li, "Ultrasound imaging using vector quantization of rf channel data," IEEE IUS, 1303-1306 (2012).
  16. S. M. Hosseini and A.-R. Naghsh-Nilchi, "Medical ultrasound image compression using contextual vector quantization," Comput. Biol. Med. 42, 743-750 (2012). https://doi.org/10.1016/j.compbiomed.2012.04.006
  17. W. R. Bennett, "Spectra of quantized signals," Bell Syst. Tech. J. 27, 446-472 (1948). https://doi.org/10.1002/j.1538-7305.1948.tb01340.x
  18. M. F. Wagdy, "Effect of adc quantization errors on some periodic signal measurements," IEEE trans. instrum. meas. IM-36, 983-989 (1987). https://doi.org/10.1109/TIM.1987.6312595
  19. G. Montaldo, M. Tanter, J. Bercoff, N. Benech, and M. Fink, "Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 56, 489-506 (2009). https://doi.org/10.1109/TUFFC.2009.1067
  20. J. Jensen, "Field: A program for simulating ultrasound systems," Medical and Biological Engineering and Computing, 34, 351-353 (1997).
  21. J. Tian, Q. Liu, X. Wang, P. Xing, Z. Yang, and C. Wu, "Application of 3d and 2d quantitative shear wave elastography (swe) to differentiate between benign and malignant breast masses," Sci. Rep. 7, 1-9 (2017). https://doi.org/10.1038/s41598-016-0028-x